Blockchain and Distributed Ledger Technologies

Blockchain and Distributed Ledger Technologies (DLT) represent a paradigm for maintaining a decentralized and synchronized digital record across a network of computers. At its core, a DLT is a replicated, shared database where participants collectively maintain and validate the ledger without a central authority, relying on consensus algorithms to agree on the state of the record. Blockchain is the most well-known type of DLT, structuring data into a chronological chain of cryptographically linked blocks, which creates an immutable and tamper-evident history of transactions. This architecture provides a robust and fault-tolerant foundation for applications requiring trust, transparency, and security in a distributed environment, such as cryptocurrencies, supply chain management, and digital identity systems.

1. Fundamentals of Distributed Systems
   1. Overview of Distributed Systems
      1. Definition and Characteristics
      2. Historical Context and Evolution
      3. Benefits of Distribution
      4. Challenges in Distributed Systems
   2. Network Topologies
      1. Centralized Networks
         1. Single Point of Control
         2. Advantages and Limitations
      2. Decentralized Networks
         1. Multiple Control Points
         2. Hierarchical Structure
      3. Distributed Networks
         1. No Central Authority
         2. Mesh Architecture
      4. Hybrid Topologies
   3. Peer-to-Peer (P2P) Networks
      1. Architecture and Communication
      2. Node Discovery and Routing
      3. Advantages and Disadvantages
      4. Examples of P2P Systems
      5. Structured vs Unstructured P2P
   4. Fault Tolerance in Distributed Systems
      1. Types of Failures
         1. Crash Failures
         2. Omission Failures
         3. Byzantine Failures
      2. Redundancy and Replication
      3. Failure Detection and Recovery
      4. Consensus in the Presence of Faults
   5. The Byzantine Generals' Problem
      1. Problem Statement
      2. Byzantine Fault Tolerance (BFT)
      3. Solutions and Limitations
      4. Practical Applications
   6. State Machine Replication
      1. Concept and Purpose
      2. Deterministic State Machines
      3. Replication Protocols
      4. Consistency Models
   7. CAP Theorem
      1. Consistency
      2. Availability
      3. Partition Tolerance
      4. Trade-offs and Implications